To test the performance of the proposed method, we employ the subjective point cloud assessment database (SJTU-PCQA) [1]} and the Waterloo point cloud assessment database (WPC) proposed by [2]} for validation. The SJTU-PCQA database includes 9 reference point clouds and each point cloud is corrupted with seven types of distortions (compression, color noise, geometric shift, down-sampling, and three distortion combinations) under six strengths, which generates 378 = 9\(\times \) 7\(\times \) 6 distorted point clouds in total.
The WPC database contains 20 reference point clouds and augmented each point cloud with four types of distortions (down-sampling, Gaussian white noise, Geometry-based Point Cloud Compression (G-PCC), and Video-based Point Cloud Compression (V-PCC)), which generates 740 = 20\(\times \) 37 distorted point clouds.
